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Sci-Vis Framework

SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highly complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states

Arthur Bleeker, PNNL↗

GLIMPSE of Future Power Grid Models

Power grid is one of the critical national infrastructures with social, economics, and national security impacts. Particularly, power distribution systems represent part of the infrastructure between power distribution substations and customers such as residential, commercial, and industrial. To address various grid modernization challenges, state-of-the-art algorithms and methodologies have been developed to deploy, operate, and expand a secure and resilient power grid. At the same time, there is a need to develop capabilities to assist power grid stakeholders to quickly get insight into the design and structure of the grid. Data visualization is a key approach to comprehend and understand complex systems such as the power grid. We present GLIMPSE Grid Layout Interface for Model Preview and System Exploration), a graph-based semantic-aware application to visualize and update distribution power grid models. The GLIMPSE can be used with standard IEEE models to search and highlight power grid objects such as generators, loads, overhead lines, etc. Additionally, it supports updating attributes and model export to integrate with GridLAB-D simulations.

Cybersecurity, power grid, visualization↗

Experimental and numerical validation of an ultrasonic visualization system for nuclear reactor application

This paper deals with the design of ultrasonic imaging systems for the next generation of nuclear reactors cooled by liquid metal. Indeed, a generation IV research nuclear reactor is being developed by the Belgian Nuclear Research Center (SCK-CEN) in the frame of the MYRRHA project (for Multipurpose hYbrid Research Reactor for High-tech Applications). This sub-critical/critical reactor is cooled by Lead-Bismuth Eutectic (LBE). The opacity of this liquid metal requires the development of an ultrasonic visualization system for internal inspection and object detection. But due to the peculiar conditions met in the core of the reactor, velocity as well as temperature gradients are expected and are likely to affect directly the ultrasonic propagation. The objective of this work is to validate the ultrasonic imaging strategy by tests performed in a dedicated test rig and by numerical simulations using a ray-tracing method. The experimental investigations have been performed on a specific water facility reproducing conditions similar to those encountered in the core of the MYRRHA reactor. These conditions include the propagation over large distance, and the presence of temperature and velocity gradients. In the MYRRHA reactor application, the distance to be travelled by the acoustic waves of the visualization system is about 5 m, including a reflection. The acoustic absorption, the scattering losses, the beam divergence and the transmitted energy during reflection have been determined as a function of the travelled distance. The experimental values are compared with the literature for validation. The presence of temperature and velocity gradients in the core of the reactor is due to the coolant circulation. These gradients are about 5 K over 0.1 m and 1 m/s over 0.2 m, respectively, and are reproduced in the facility for investigating their influence on the propagation of ultrasounds. The experimental data are used for improving and validating a ray-tracing algorithm. This algorithm is then applied to the full scale application for validating the ultrasonic visualization system for nuclear reactor application. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

VTK-m User's' Guide (V.1.7)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.This book includes contributions from the VTK-m community including the VTK-m development team and the user community.

97 MATHEMATICS AND COMPUTING↗

VTK-m User's Guide (V.1.8)

Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

The VTK-m Users' Guide (V.1.9)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

The VTK-m Users' Guide (V.2.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

Innovative Patient Room Lighting System with Integrated Spectrally Adaptive Control

In December of 2013, the U.S. Department of Energy’s SSL R&D Program released a Funding Opportunity Announcement (FOA), that for the first time, contained opportunities for comprehensive application-specific system development. The FOA included opportunities for two applications, one of which was a Patient Room. Philips Lighting Research North America, submitted a proposal for the Patient Room application, and was selected for the complete project award. The award amount was for $497,127, with a Philips Research co-funding commitment 165,709 dollars. The total project value was 662,836 dollars. This project sought to redefine lighting for the patient room application. The goal was to deliver an innovative LED patient suite (patient room and bathroom) lighting system solution that was 40% more energy-efficient than traditional fluorescent incumbent technologies, and would meet all the visual and non-visual needs of patients, caregivers and visitors, and improve the patient experience. State-of-the-art multichannel LED platforms and control technologies that would provide spectral tuning and become part of an intelligent, connected lighting system drove the solution. The project was scoped into four main task areas that included a) System Concept Creation, b) Identification of the Luminaire Portfolio, c) Development of the Connected Lighting Infrastructure, and d) System Performance Validation. Each of the four main tasks were completed and validated extensively over the course the 2 ½ year project. The system concept was created by first developing a lighting design that demonstrated best practices for patient room lighting – illuminance and uniformity for task performance, reduced glare, and convenient controls, in addition to giving patients control over the lighting in their environment. A framework was defined to deliver circadian support via software behaviors. Through that process luminaires were identified from the Philips portfolio that were adaptable – by their form, dimensions, and optical materials – to mix multicolor LED platforms uniformly and deliver target design lumen levels. The Blue Sky luminaire was selected for the patient bed area to give the illusion of skylight while providing white light on the patient bed. Luminaires used existing 2-channel tunable white LED boards, and newly developed 4-channel LED boards. Red-Orange, Blue, Green, and Blue-shifted Yellow LED chips were selected based on spectral characteristics and their ability to produce high quality white light. 4-channel Power over Ethernet (PoE) drivers were developed and firmware written so they would communicate with both 2- and 4-channel boards. These components formed the backbone of the connected lighting infrastructure. Software, flexible and nuanced in its complexity, was written to set behaviors for myriad lighting scenes in the room throughout the 24 hour day – and all could be overridden by manual controls. This included a dynamic tunable white program, three color changing automatic programs that simulated degrees of sunrise to sunset palettes, and an amber night lighting system that offered visual cues for postural stability to minimize the risk of falls. All programs were carefully designed to provide visual comfort for all occupants, support critical task performance for staff, and to support the patient’s 24hr rhythms. A full scale mockup room was constructed in the Philips Cambridge Lab. The lighting system was installed, tested and functionality demonstrated to ensure smooth operation of system components – luminaires, drivers, PoE switches, wall controls, patient remote, and daylight and occupancy sensors. How did the system perform? It met visual criteria, confirmed by calculations, simulations and measurements in the field. It met non-visual criteria, confirmed by setting circadian stimulus (CS) targets and performing calculations using the calculator developed by the Lighting Research Center. Finally, human factors validation studies were conducted to gain insight from real end users in the healthcare profession; surveys were administered, data analyzed, and audio comments captured. The general consensus was positive, with requests to pilot the system in their hospitals. The importance of the research completed under this grant is that it allowed the exploration and development of a unique lighting system, one that would deliver a blend of visual and non-visual criteria in patient room design for today’s healthcare environment. The research investigated the area of multichannel LED technology, multichannel Power over Ethernet (PoE) drivers and their integration with automatic and manual controls as a system – uncovering and meeting challenges along the way. It married visual needs of patients and staff with support for 24 hour rhythms, placing value on the wellbeing of the patient – while successfully saving energy over incumbent technologies. Indications are that the market is ready and willing to invest – multiple healthcare facilities are in line to pilot this system, recognizing its value beyond energy to patient and staff well-being. Its value to the public can best be expressed by a patient support coordinator who, after spending several hours in the room being immersed in the lighting, analyzing all its features, commented: “This re-writes lighting for healthcare”.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Visual Comparison of Silent Error Propagation

High-performance computing (HPC) systems play a critical role in facilitating scientific discoveries. Their scale and complexity (e.g., the number of computational units and software stack) continue to grow as new systems are expected to process increasingly more data and reduce computing time. However, with more processing elements, the probability that these systems will experience a random bit-flip error that corrupts a program's output also increases, which is often recognized as silent data corruption. Analyzing the resiliency of HPC applications in extreme-scale computing to silent data corruption is crucial but difficult. An HPC application often contains a large number of computation units that need to be tested, and error propagation caused by error corruption is complex and difficult to interpret. Here, to accommodate this challenge, we propose an interactive visualization system that helps HPC researchers understand the resiliency of HPC applications and compare their error propagation. Our system models an application's error propagation to study a program's resiliency by constructing and visualizing its fault tolerance boundary. Coordinating with multiple interactive designs, our system enables domain experts to efficiently explore the complicated spatial and temporal correlation between error propagations. At the end, the system integrated a nonmonotonic error propagation analysis with an adjustable graph propagation visualization to help domain experts examine the details of error propagation and answer such questions as why an error is mitigated or amplified by program execution.

97 MATHEMATICS AND COMPUTING↗

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying models of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.

active data↗

The VTK-m User's Guide (V. 2.2)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗

Niowave Flow Testing of the High Power Converter - FY 21

Design work for a 100 kW converter to produce a neutron flux via electron impact on a flowing stream of liquid metal lead-bismuth (LBE) was conducted in FY20. In FY21, the focus shifted to a 20 kW converter which was designed in collaboration with Niowave engineers. A flow visualization model is needed to validate model results for the 20 kW converter and ensure adequate coolant flow over containment structures. This work highlights the mockup that was made with quartz side plates by LANL.

42 ENGINEERING↗

Study of the flow mixing in a novel ARID raceway for algae production

A novel flow field for algae raceways has been proposed, which is fundamentally different from traditional paddlewheel-driven raceways. To reduce freezing and heat loss in the raceway during cold time, the water is drained to a deep storage canal. The ground bed of the new raceway has a low slope so that water, lifted by propeller pump, can flow down in laterally-laid serpentine channels, relying on gravitational force. The flow rate of water is controlled so that it can overflow the lateral channel walls and mix with the main flow in the next lower channel, which thus creates a better mixing. In order to optimize the design parameters of the new flow field, methods including flow visualization, local point velocity measurement, and CFD analysis were employed to investigate the flow mixing features. Different combinations of channel geometries and water velocities were evaluated. An optimized flow field design and details of flow mixing are presented. The study offers an innovative design for large scale algae growth raceways which is of significance to the algae and biofuel industry.

09 BIOMASS FUELS↗

CIEL ∗ Ch color map for visualization and analysis of sea ice motion

The International Commission on Illumination (CIE) designed its color space to be perceptually uniform so that a given numerical change in the color code corresponds to perceived change in color. This color encoding is demon- strated to be advantageous in scientific visualization and analysis of vector fields. The specific application is analysis of ice motion in the Arctic where patterns in smooth monthly-averaged ice motion are seen. Furthermore, fractures occurring in the ice cover result in discontinuities in the ice motion. This vector jump in displacement can also be visualized. We then analyze modeled and observed fractures through the use of a metric on the color space, and image amplitude and phase metrics. Amplitude and phase met- rics arise from image registration that is accomplished by sampling images using space filling curves, thus reducing the image registration problem to the more reliable functional alignment problem. We demonstrate this through an exploration of the metrics to compare model runs to an observed ice crack.

97 MATHEMATICS AND COMPUTING↗

A New Default Colormap for ParaView

ParaView is one of the most prominent software tools for scientific visualization used by scientists around the world. Color is a primary conduit to visually map data to its representation and, thus, enable investigation and interpretation of the data. Colormap selection has a significant impact on the data revealed; its design and selection is a critical aspect of scientific data visualization. A common choice for a user is the program’s default colormap, so careful consideration of this default is consequential. Although the current default colormap in ParaView, a succession of hues from cool blue to warm red, has served the community well, research shows that more nuanced colormap configurations increase discriminability while maintaining other critical metrics. These findings inspire us to revisit and update the default colors in ParaView. Here, in this study, we present a new ParaView default colormap, the criteria and methods of development, and example visualizations and analytic metrics.

97 MATHEMATICS AND COMPUTING↗

Model-Based Energy and Cost Analysis of Direct Air Capture Using ePTFE-Based Laminate-Structured Gas–Solid Contactors

Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗